Conspiracy and dishonesty in climate science

Over the last few days a debate has taken place in the comments on this website, the core of its being that the paper on measuring global temperature I had referred to was an example of ‘conspiracy theory’. Those who thought so seemed to equate ‘dishonesty’, a term used from time to time in the paper, with ‘conspiracy’. I didn’t think that was reasonable, and this post is devoted to the difference, and what can fairly be said about the status of climate science with respect to these two terms.

‘Conspiracy’ is simpler to deal with than ‘dishonesty’ so I’ll discuss it first. My Shorter OED defines ‘conspiracy’ as ‘a combination of persons for an evil or unlawful purpose’. You will find people in the blogosphere talking about climate scientists as though they were conspirators, but I think that is far-fetched, and usually unnecessary. There is a useful bonmot from the public service, ‘if you have to choose between a conspiracy and a stuff-up, choose the stuff-up every time’. In the climate science case, ‘if you have to choose between a conspiracy and groupthink, choose groupthink every time.’

Having said that, there is no doubt that there was a group of climate scientists who referred to themselves as ‘The Team’ (they may still do so), and behaved in what I would have called a conspiratorial way. You can read about them in Climategate. The CRUtape letters by Mosher and Fuller. They united to prevent papers critical of their own being published, did their successful best to have sacked a journal editor who did not do as they wished, and did all this in secrecy. It was the release of their emails that gave their deeds away. Was what they did an example of ‘an unlawful purpose’? No, but it was underhand and grubby, and not at all consistent with the established tenets of natural science, where peer review is there to ensure that what is published in the journals has passed through an ethical and impartial system.

The sciences represented by IPCC Working Group I do not share common principles for such basic tasks as visualizing data, interpreting anomalies, representing uncertainty, data-sharing, or public disclosure. That such disparate communities have come to agree on the causes, size, and scope of the climate problem, through iterative rounds of assessment, may be taken as strong evidence of reliability. At the same time, the very fact that judgment has been integrated across many fields leaves climate science vulnerable to charges of groupthink and inappropriate concealment of uncertainties.

‘Dishonesty’ is altogether more slippery a term, because there is no established standard for ‘honesty’ in science, other than the expectation that presented data have not been faked. What we have, for the most part, are exhortations, from people like Richard Feynman and Karl Popper, to the effect that a scientist ought to be her own severest critic, because the easiest person to fool is oneself. The general standard in journals is that all the necessary data and working out are either in the paper or readily available. The peer-review system is supposed to weed out shoddy and careless work, but much peer review seems to be slight. Since to review any paper properly takes time and energy, and these are resources in short supply for most academics, that is not surprising.

The most obvious example of what is commonly called intellectual dishonesty is Dr Mann’s ‘hide the decline’ device on the ‘hockey stick’ graph, where a set of proxies used to estimate global temperatures up to the present was replaced by thermometer temperatures in the recent period. Why not? you might ask. Aren’t they better than the proxies? Yes, they are. But the proxies actually showed a cooling for the recent period, and that suggests that the proxies are not very reliable indicators of past temperatures either. In short, the graph meant nothing. If all this is new to you, then listen to Professor Richard Muller of Berkeley explain it all here. He is someone who thinks that the world is warming and that human beings have had something to do with it. (As it happens, so do I, but I doubt that we can be sure humans have had much to do with it.)

Now Dr Mann has indignantly denied that he has done anything wrong, and indeed he is in the process of suing someone who has called his work fraudulent. More, he writes again and again proclaiming that the world is in crisis over ‘climate change’ and that, in summary, everyone who disagrees with him is a denier or ignorant or a stooge for big oil. Plainly, he does not think that he has been dishonest. In commercial matters a court would be given the job of determining ‘dishonesty’ in a transaction. And despite a recent suggestion that there should be an International Court to deal with the facts about ‘climate change’, there is no current process for adjudicating on such issues.

That means that we are all free to decide what we think. I am on the side of Feynman and Popper. One needs to look critically at one’s own work. Because I am a data-grubber, and think that measurements are important, and that the processes for measuring are even more important, I think that entities that have the task of presenting basic data to the public, as the result of public expenditure for that purpose, have an obligation to do so as scrupulously as possible, and not to ‘spin’ the outcome to suit the purposes of the current government. In Australia I think the ABS does that very well. I am much less confident about the Bureau of Meteorology.

As to the IPCC, its charter obliges it to look not at climate change — all the factors that go to influence the various climates of the planet — but at ‘climate change’ — the effect of human activity on climate. The IPCC cannot be faulted for disregarding natural variability or, rather, for not starting with natural variability and then looking at human influences. Its charter is its defence. It can’t be said to be ‘dishonest’ in doing what it does, at least in my judgment. But I can nonetheless argue, and I do, that its approach to climate is consequently one-eyed and inclined to error.

Professor Muller says, in his little talk, that he would not take seriously any papers written by those who were associated with the ‘hide the decline’ graph. And I agree. They cannot be trusted. Trust is vital in all this. I don’t think that the IPCC is dishonest. But I do not think it can be trusted. Following Jasanoff, above, I think that there is far too much concealment of uncertainties. And if people go on writing papers in which they don’t even consider the other possibilities with respect to their argument, I don’t trust their work much either.

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Conspiracy tends to suggest a small secretive cabal engaged in some illicit agenda. Although this might arguably be applied to the activities of “the team” revealed in the Climategate emails there is now endemic to climate science a lesser form of secretive impropriety of the wink and a nod variety. This is manifest in a widespread and obvious use of provably false claims, exaggerated certainty, unexplained data “adjustments”, personal denigration of critics, suppression of conflicting evidence and sundry other malpractices. The informal conspiratorial aspect is apparent in both the lack of any questioning or condemnation of even the most apparent malpractice and, even worse, the attempt to deny, excuse or trivialise it.

The idea that the peer review employed by scientific journals is an assurance of quality and validity is largely a fabrication of the self-proclaimed climate experts to enhance their own claim to authority. The real peer review in science comes after publication and, to a lesser extent, before submission for publication when most authors send manuscript copies to respected colleagues for their comments. The primary reason for the peer review used by journals is simply that editors are in no position to judge the validity and importance of much of what they publish. They need the advice of someone they consider an expert in the subject. Usually, this is someone whose own work they have published before. The result is that certain journals often become favourable to research supporting particular positions in matters of controversy.

Yes. I think there is an unwillingness on the part of organised science (and individual scientists) (i) to criticise some of the worst aspects of it all, because it might make ‘science’ look bad, reduce funding, etc, and (ii) to raise one’s head above the parapet, unless criticism is directed at you, and funding is reduced for you.

You said ‘In the climate science case, ‘if you have to choose between a conspiracy and groupthink, choose groupthink every time.’ Looking at the Wikipedia entry for groupthink it quotes William H Whyte Jr. from 1952: “What we are talking about is a rationalized conformity – an open, articulate philosophy which holds that group values are not only expedient but right and good as well.” This sounds like a nice description of “noble cause corruption” to me, which has been frequently used to describe the pro-CAGW antics. Maybe this explains what’s going on better than simply dubbing it a “conspiracy”.
(BTW – I think you are far too generous in responding to the baits of the likes of “David” and “JimboR”. My reading of their posts (and their persistent “non-understanding” of your comments) makes me think that they are at best time-wasters, or worse, working to a script. In either case IMO they are not intent on sharing their views, but merely disrupting your blog for their own ends.) Otherwise, thanks for your blog and best wishes.

I don’t like to ignore comments that raise issues, but I’m beginning to think that I should use Judy Curry’s rule and not engage with comments that are not directly relevant to the essay. Errors and omissions on my part would always get a response.

But today let’s move the discussion away from climate change just for a moment. Show me a paper that you like, which looks at something other than global temperature (e.g. share prices or coal exports, student enrollments or whatever you like) that uses the methodology you describe, so I have some idea of what you actually mean .

I have enough to do without helping you to understand what I mean, when it seems to be understood by others. I haven’t had any other complaints either here or via email.

Let’s just say that variability must be composed of elements that include human factors and other-than-human factors. It would seem sensible to set the human factors in the context of the other-than-human ones, to avoid imagining that the human ones explain everything. That’s about the best i can do for you.

With all due respect, your first paragraph comes across as just a little bit evasive.

If your methods are as sensible as you claim surely they have been used to elsewhere in the scientific literature. You should be able to post a couple of links to some non-climate change papers which use the methods you describe.

You rarely engage in substance, David, and seem to love to nitpick. As it happens you are the only person who professes not to understand. Perhaps this will help.

Here is an image of carbon dioxide and temperature. There are lots of these, and much depends on how you locate the axes. In the case of CO2, the data prior to 1960 are drawn from various sources, from 1960 on from Mauna Loa. But no matter. The two lines have a similarity, but plainly CO2 doesn’t explain everything. What is missing? Something else, which we call ‘natural variability’ Some aspects of it, like cycles of various lengths, have been posited. The IPCC itself says it has low knowledge of the affects of clouds. And so on. The point is that far too much attention has been given to CO2, and the models that have been generated seem to give it too much power. Yes, we wait for someone to do the work. The money, alas, is going to other attempts to show how important CO2 is.

I don’t feel it is “nit picking” to ask you to describe your proposed method. I simply asked you to provide a few examples of how your proposed approach has been used in other areas of research and you have not done so.

I too am not sure how Science-according-to-Don would work. It sounds like he’s proposing all research should start with a blank piece of paper and a blank mind. Rather than build on prior discoveries they should start afresh and assume nothing. One of his often cited complaints is that scientists always start from the position of X.

In the real world, science mostly consists of taking little steps on top of all the thousands of steps taken by other scientists before you. Every once in a while when you do that, you’ll discover something that changes everything and blows away all those earlier steps.

Contrary to Don’s claims that scientists don’t want to “make ‘science’ look bad” or “raise one’s head above the parapet” all the scientists I know dream of being the one to make one of those revolutionary discoveries. Many of the papers I read are direct attacks on the orthodox models. I see no evidence of scientists being shy, and Don offers none.

“Many of the papers I read are direct attacks on the orthodox models. I see no evidence of scientists being shy”
Are you talking about climate science or other fields?
I’m sure in other areas the contrary researchers aren’t labelled deniers.

Other. True, they’re not labelled deniers, but they are considered fringe dwellers, at least until they come up with the goods. The only remedy for bad science is good science. Don’s scenario of hundreds of climate scientists all thinking “we better keep their heads down lest they come for us too” is laughable.

I know (from personal experience) that good connections make for a successful career. No guy, (and scientists are quite ordinary people) is going to stick his head above the parapet if, in doing so, he is going to place his mortgage, children’s schooling, chances of renewal/tenure, etc, at risk. You can talk all you like, but that’s the reality of life in the fast lane.

Don, these are my concerns about the way you conceptualize “natural variability “ into your understanding of climate science.

Here are two very basic climate models.

(1) Temp = f (CO2,…)

(2) Temp = f (CO2, NV,…)

NV = natural variability

The first model explains temp with CO2, the second adds a
variable natural variability to explanatory variables. Even though Model 2 may explain more of the total variation in Temp (i.e. R squared) any change in the size of coefficient on CO2 remains an open question. There are three
possibilities.

1. If NV is uncorrelated with CO2, then adding NV
to model will have no effect the CO2 coefficient.

2. If NV is correlated the size of coefficient
on

a. CO2 could increase

b. CO2 could decrease

Adding NV to the model would be a good, for its own sake.
But it is just wishful thinking on your part to assume that doing so would necessarily decrease the effect that CO2 has on temp. There is just as much chance that the size of the CO2 coefficient could increase.

Au contraire as they say at the SCM. I think we owe David much gratitude for sifting through a lot of this stuff and calling it for what it is. Most of us with any scientific knowledge get about a paragraph in, have a chuckle, and click on to something else.

As an example… following a misguided lead from the SCM, Don recently declared arithmetic means no longer useful for measuring temperatures while studying AGW. Why? Because we humans typically only experience the mean briefly twice a day. David called that out for the nonsense that it is. Don just “shrugged and kept writing”.

Given his pedigree it’s very hard to believe that Don was stupid enough to believe that. The only other alternative I can think of is that he is practising some of the very scientific dishonesty he accuses real climate scientists of.

The only stupid thing Don did was rise to David’s bait. This is becoming a game of see if we can trip up the Professor. Really childish antics.
I thought the French paper was quite a poor effort and called out one part. The bit on mean temperatures you and David highlight is nothing more than nit picking designed to needle Don.

Needling Don is certainly not my goal. Lest we forget, when the debate kicked off Don went in in full support of the SCM position…. telling us all about Canberra weather.

I’m not sure I’ve ever seen a better example of dodgy science being positively reviewed by others. And we still don’t know why. Was it scientific dishonesty? Was it a temporary brain snap? Does Don still support their position? We’ll never know because when the going gets tough Don “shrugs and moves onto the next essay”.

The climate change issue reminds me of court case. CO2 is in the dock being charged with the offence of raising the earth’s temperature, if found guilty the severity of CO2’s sentence will depend on the amount warming it has produced. Those activists on the prosecuting team are not in the least interested whether “others” e.g. natural factors are involved, whether partially or wholly. Their brief is to nail CO2 and ensure it gets a severe sentence, hence the only evidence that fits the prosecution’s case is produced.

Sure, the prosecution may have doubts or even knowledge that CO2 is not as bad as they make out, but that is not their job, theirs is to highlight the negative side of CO2’s character. Unfortunately in this lopsided court case, witnesses for the defence have been given little opportunity to air their evidence.

Here’s a recent post from Judith Curry about the pause. You’ll note the IPCC AR 5 trend from 1951 to 2012 is 2.4 times greater than the trend from 1998 to 2012. That’s 0.12 C per decade compared to 0.05 C per decade. I would guess that co2 in 1950 was about 310ppm and in 1990 it was about 350 ppm. Food for thought anyone? This is how she starts the first couple of paragraphs.

“Hiatus controversy: show me the data

Posted on November 6, 2015 | 533 Comments

by Judith Curry

The scientific and political controversies surrounding the hiatus have continued to heat up. Lets take a look at ALL the global temperature data sets.

So, what is the ‘hiatus’ or ‘pause’ or ‘slowdown’, and why does it matter? Here are three criteria for the hiatus to matter:

1) the rate of warming over a particular period of at least 10 years is not statistically significant from zero (with the context of a nominal 0.1C uncertainty). Note the IPCC AR5 cited: “As one example, the rate of warming over the past 15 years (1998–2012; 0.05 [–0.05 to +0.15] °C per decade is smaller than the rate calculated since 1951 (1951–2012; 0.12 [0.08 to 0.14] °C per decade)”